Inactivation of Enzyme Laccase and Role of Cosubstrate Oxygen in Enzymatic Removal of Phenol from Water
Bibliographic record
Abstract
Research was conducted to evaluate the potential use of laccase and its susceptibility to inactivation in an alternative enzyme-based treatment technology to remove parent phenol from buffered distilled water. Enzymatic oxidative polymerization of phenol with laccase was carried out in continuously stirred batch reactors. The reaction products were insoluble polymers, which precipitated out of the solution once their solubility limits were exceeded. The findings demonstrated that the polymeric products had significant effects on enzyme activity consumption and subsequent phenol removal. Enzyme species present in the reaction vessel were classified into enzyme remaining in the solution (type 1) and enzyme adhering to the precipitate polymers (type 2). Type 1 enzyme was more efficient in removal of phenol from solution compared with type 2. Subsequent filtration enhanced the phenol removal by removing type 2 enzyme adhering to the polymer particles and decelerating enzyme inactivation. The study also investigated the effects of available dissolved oxygen, provided through aeration and hydrogen peroxide addition, on phenol removal. Aeration and hydrogen peroxide addition increased the dissolved oxygen concentration, but had no effect on the progress curve for phenol removal.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".